Peer-reviewed article
The LMSz method - an automatable scalable approach to constructing gene-specific growth charts in rare disorders.
Karen J Low, Julia Foreman, Rachel J Hobson, Hannah Kwuo, Elena Martinez-Cayuelas et al. ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This paper describes a statistical method for creating growth charts specific to rare genetic disorders by transforming anthropometric data to reference z-scores. The LMSz method was applied to children with six different monogenic neurodevelopmental disorders, showing that most have below-average growth patterns. The method could be automated and made available clinically to help monitor growth in children with these rare conditions.
Key points
- The LMSz method enables construction of gene-specific growth charts from smaller sample sizes than conventionally required
- Most of the six disorders studied showed below-average median height, weight, and/or head circumference compared to reference populations
- KMT2A was the only disorder showing an age-related trend in median height
- The method assumes the same skewness in reference and rare disease distributions
- The authors plan to automate the method within the DECIPHER platform for clinical use
Limitations
This is a methodological paper focused on statistical technique development rather than clinical outcomes or intervention evaluation. It does not assess whether use of these charts improves clinical care or child health outcomes.
Abstract
Children with monogenic neurodevelopmental disorders often grow abnormally. Gene-specific growth charts would be useful but require large samples to construct them using the conventional LMS method. We transformed anthropometry to British 1990 reference z-scores for 328 UK and 264 international individuals with ANKRD11, ARID1B, ASXL3, DDX3X, KMT2A, or SATB2-related disorders, and modelled mean and standard deviation (SD) of the z-scores as gene-specific linear age trends adjusted for sex. Assuming the same skewness in the reference and rare disease distributions, we then back-transformed the mean ±2 SD lines to give gene-specific median, 2nd, and 98th centiles. The resulting z-score charts look plausible on several counts. Only KMT2A shows a (rising) age trend in median height, while BMI and weight increase for several genes, possibly reflecting population trends. Apart from SATB2 and DDX3X, the gene-specific medians are all below the reference (range 0.1th centile for height KMT2A to 36th centile for BMI ANKRD11). Median OFC z-score shows no age trend, with medians ranging from 10th to 30th centile, and ASXL3 is lowest, on the 3rd centile. In 19/24 cases, the centiles for the two sexes are the same on the z-score scale. Our LMSz method produces gene-specific growth charts for rare diseases, which, when used in the correct context, could be an important clinical tool. We plan to automate it within the DECIPHER platform, enabling availability for relevant genes.